Systems and methods for automated assessment of physical objects

ABSTRACT

Described in detail herein are methods and systems for performing a physical object assessment. The system entails an automated system to receive, unpack and assess a physical object based on automated determined attributes. The system can determine an element based on the assessment and generate a webpage including the attributes of the physical object and the determined element.

CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

This application claims priority to U.S. Provisional Application No.62/361,285 filed on Jul. 12, 2016, the content of which is herebyincorporated by reference in its entirety.

BACKGROUND

Un-packaging and assessing physical objects can be a slow error proneprocess. In addition, there can be a lack of verification which maycause the physical object to be inaccurately assessed.

BRIEF DESCRIPTION OF DRAWINGS

Illustrative embodiments are shown by way of example in the accompanyingdrawings and should not be considered as a limitation of the presentdisclosure:

FIG. 1 is a block diagram of an exemplary physical object assessmentsystem according to embodiments of the present disclosure;

FIG. 2 illustrates an exemplary network environment of a computingsystem in accordance with embodiments of the present disclosure;

FIG. 3 illustrates an exemplary network environment of a computingsystem in accordance with embodiments of the present disclosure;

FIG. 4 illustrates a block diagram of the physical object assessmentsystem embodied as part of a smart auction system according toembodiments of the present disclosure;

FIG. 5 illustrates a block diagram of the physical object assessmentsystem embodied as an auction system using decentralized currencyaccording to embodiments of the present disclosure;

FIG. 6 illustrates a block diagram of the smart coin system of theauction system using decentralized currency according to embodiments ofthe present disclosure;

FIG. 7 is a flowchart illustrating the physical object assessment systemaccording to embodiments of the present disclosure; and

FIG. 8 is a flowchart illustrating the smart auction system according tothe present disclosure.

DETAILED DESCRIPTION

Described in detail herein are methods and systems for automatedphysical object assessment. Embodiments of the methods and systemsentail an automated system to receive, unpack and assess a physicalobject based on automated determined attributes. The system candetermine an element based on the assessment and generate a webpageincluding the attributes of the physical object and the determinedelement.

In exemplary embodiments, a conveyer belt is configured to receive,support, and transport physical objects. The physical objects areassociated with a machine-readable element encoded with identifierscorresponding to the physical objects. A scanner is disposed withrespect to the conveyer belt and configured to scan the machine-readableelements of the physical objects and decode the machine-readableelements to extract the identifiers. An image capturing device disposedwith respect to the conveyer belt and configured to capture images ofthe physical objects. A scale is operatively coupled to the conveyerbelt and configured to determine weights of the physical objects.

A computing system, including a server and a database, can beoperatively coupled to the scanner, the image capturing device, and thescale. The computing system can be programmed to query the databaseusing the identifiers extracted from the machine-readable elements bythe scanner to retrieve information regarding the physical objects fromone or more tables in the database. The computing system extracts setsof attributes associated with the physical objects from the images ofthe physical objects and identifies elements associated with thephysical objects based on the retrieved information regarding thephysical objects, the sets of attributes associated with the physicalobjects and the weights of the physical objects. Furthermore, thecomputing system, can create webpages including the information, thesets of attributes associated with the physical objects, and theelements.

FIG. 1 is a block diagram of an exemplary physical object assessmentsystem 112 according to the present disclosure. The physical objectassessment system 112 can provide an autonomous intake process foridentifying and assessing physical objects and for automaticallycreating webpages for the physical objects based on the identificationand assessment of the physical objects. The physical object assessmentsystem 112 includes a conveyer belt 100, a scale 102, image capturingdevice(s) 104, a reader(s) 110, autonomous robot pickers 108 a-b and anx-ray machine 120. The scale 102, the image capturing device(s) 104, thereader(s) 110, and the x-ray machine 120 of the physical objectassessment system 112 can be in communication with one or more computingsystems that can receive data from the scale 102, image capturing device104, reader(s) 110, and an x-ray machine 120 to facilitate the intakeand assessment processes described herein and to generated webpages forthe physical objects that are processed via the intake and assessmentprocesses. Exemplary computing systems are described herein, forexample, with reference to FIGS. 2-5. In exemplary embodiments, thephysical object assessment system 112 can receive packaged physicalobjects (e.g., physical object 118) on a conveyer belt 100, removepackaging from the physical objects and assess the physical objectsbased on attributes determined using an image capturing device 104,reader 110 and a scale 102 as the physical objects are transported bythe conveyor belt 100. In exemplary embodiments, the physical objectscan be enclosed in packaging and at least one machine-readable elementcan be affixed to the packaging enclosing each physical object. Thephysical objects (e.g., the physical object 118) enclosed in thepackaging (e.g., packaging 106) can be associated with machine-readableelements (e.g., machine-readable element 116). The machine-readableelements can be encoded with identifiers corresponding to the physicalobjects enclosed in the packaging (e.g., the identifier encoded in themachine-readable element 116 affixed to the packaging 106 can correspondto the physical object 118 enclosed in the packing 106). The packaging106 can be of different materials such as cardboard or plastic. Themachine-readable element 116 can be a barcode, QR code, an/or an RFIDtag.

The conveyer belt 100 can be formed by one or more belts operativelycoupled to one or more belt cabinets 114, which may include rollers(e.g., friction and drive rollers) and a drive motor. The driver motorcan control one or more of the rollers to rotate the belt to provide atransport for moving items along a length of the conveyor belt 100 fromone end of the conveyor belt 100 to an opposite end of the conveyor belt100. The image capturing device 104, the scale 102, the autonomous robotpicker 108 a, the reader 110, and x-ray machine 120 can be disposed atstations positioned at different locations along the length of theconveyor belt 100. The conveyor belt 100 can transport the physicalobject from station to station so autonomous intake and assessmentprocesses can be implemented at the stations. For example, the conveyorbelt 100 can transport the packaged physical object to a first station,which can include the reader(s) 110 to scan the packing formachine-readable elements; a second station, which can include the x-raymachine 120 to examine the contents in the packaging; a third station,which can include the autonomous robot picker 108 a to unpack thephysical object from the packaging; a fourth station, which can includea scale 102 to weigh the physical object after it is unpacked; and afifth station, which can include the image capturing device(s) 104 tocapture one or more images of the physical object.

Upon placing the packaged physical object 118 on the conveyor belt 100,the conveyor belt 100 can transport the packaged physical object 118 tothe reader(s) 110. The reader(s) 110 can read the machine-readableelement 116 affixed to the packaging 106 and can decode themachine-readable element 116 to extract the identifier. The reader(s)110 can be disposed above or to a side of the conveyer belt 100 and/orcan automatically move or be repositioned with respect to the conveyorbelt 100 (e.g., can be operatively coupled to a track and can be movedwaling the track). In some embodiments, the system can include a singlereader 110 or multiple readers 110 at different positions and/ororientations to facilitate scanning of machine-readable elements locatedin different positions on packaging 106. In some embodiments, one ormore mirrors can be disposed about the conveyor belt 100 at the stationthat includes the reader(s) 110. For embodiments in which the reader(s)are implemented as optical readers, the mirrors can be positioned toreflect light (e.g., infrared light) output by the reader(s) and/orreflected from one or more surfaces (e.g., a surface of the package) toread machine-readable elements disposed in different positions onpackages. The reader(s) 110 can be configured to extract encodedinformation from machine-readable element 116 and decode the encodedinformation such as the identifier associated with the physical object118. The identifier can be transmitted from the reader(s) 110 to one ormore computing systems to facilitate intake and assessment of thepackaged physical object 118. For example, the one or more computingsystems can identify the physical object 118 that should be included inthe packaging 106 based on the identifier received from the reader(s)110 and can retrieve attributes associated with the physical object 118.If no machine-readable identifier is found on the packaging, anindication that the reader(s) 110 failed to read a machine-readableidentifier can be transmitted to one or more computing systems.

The packaged physical object 118 can be transported from the stationincluding the reader(s) 110 to the station including the X-ray machine120 by the conveyor belt 100. The packaged physical object can be passedthrough the X-ray machine 120, which can detect the contents within thepackaging 106 and can capture x-ray two-dimensional and threedimensional images of the contents of the packaging 106 from differentperspectives, which can be used to determine whether the physical object118 enclosed within the packaging 106 is missing and/or damaged and/orcan be used to determine whether all of elements or components of thephysical object are included in the packaging 106. For example, thex-ray images can be transmitted to one or more computing systems and theone or more computing system can compare the x-ray images to a set ofx-ray images retrieved from one or more databases based on theidentifier read by the reader(s) 110. When no identifier has been found(e.g., the reader(s) 110 fail to read a machine-readable element), thex-ray images can be used by the one or more computing systems toidentify types of objects included in the packaging 106 and/or whetherthe physical object may be damaged. In response to a determination thatthe physical object is or may be damaged or is missing elements based onthe x-ray images, the one or more computing system can transmit an alertand/or divert the package to another conveyor belt to be processed forreturn to the sender or for manual processing.

The packaged physical object 118 can be transported from the stationincluding the X-ray machine 120 to the station including the autonomousrobot picker 108 b by the conveyor belt 100. The physical object 118 canbe unpackaged by the autonomous robotic picker 108 a. Furthermore, thephysical object can be placed and removed from the conveyer belt 100using the autonomous robot picker 108 b. For example, the autonomousrobot picker 108 b can be in the at a front end of the conveyer belt 100and/or the distal end of the conveyer belt 100 to place the physicalobject and/or to remove the package from the conveyer belt 100. Theautonomous robot pickers 108 a-b can be, but are not limited to,driverless vehicles, unmanned aerial vehicles (e.g., drones), and/or anyother suitable autonomous robot configured to autonomously perform thefunctions, operations, and actions described herein. The autonomousrobot picker 108 a can detect the arrival of the packaged physicalobject 118 and remove the packaging 106 (e.g., using one or morearticulated arms of the autonomous robot picker 108 a).

The unpacked physical object 118 can be transported from the stationincluding the autonomous robot picker 108 b to the station that includesthe scale 102. The scale 102 can be embedded in or under the conveyerbelt 100 to weigh the unpacked physical object 118. The scale 102 can bean electronic weighing machine configured to determine a weight of thephysical object 118 on the conveyer belt. The scale 102 can be an analogor digital scale that calculates the weight of objects using one or morestrain gauges, piezoelectric devices, pressure sensors, or othersuitable devices that can convert a force applied to the scale by anobject (e.g., from gravity) to an electrical signal representative ofthe force. The output of the scale can be transmitted to one or morecomputing device to facilitate the intake and assessment processesdescribed herein.

The unpacked physical object 118 can be transported from the stationincluding the scale 102 to the station that includes the image capturingdevice(s) 104 by the conveyor belt 100. The image capturing device(s)104 can be disposed with respect to the conveyer belt 100 to capture oneor more images of the unpacked physical object 118. The image capturingdevice(s) 104 can be disposed above or to the side of the conveyer belt100. In some embodiments, the system can include a single imagecapturing device 104 or multiple image capturing devices 104 atdifferent positions and/or orientations to facilitate capturing imagesof the physical object at different orientations and positions. In someembodiments, the image capturing device 104 can be configured to move tocapturing images of the physical object from different orientationand/or positions. The image capturing device 104 can be a camera and cancapture still images or moving images of the physical object 118. Theimage(s) captured by the image capturing device(s) 104 can betransmitted to one or more computing system to facility the intake andassessment processes described herein.

In some embodiments, the physical object assessment system 112 caninclude ultraviolet light sensors (not shown) for inspection of artworkand collectibles (e.g., to identify forgeries and/or fraudulent works).

In some embodiments, the physical object assessment system can includemolecular scanners (not shown) using a near-IR spectroscopy method todetermine the contents of a physical object. The interaction of thevibration of molecules can be detected and referenced to a database ofmolecular compositions and vibrations. Using the detected vibration ofthe molecules the computing system 200 can determine the contents withinthe packaging. As a non-limiting example, molecular scanners can be usedfor determining the contents of the following physical objects:pharmaceuticals, food, beverages, art, collectibles, and jewelry.

FIG. 2 illustrates an exemplary distributed computing system in anetwork environment 240. The environment 240 can include one or morecomputing systems 200, one or more servers 210, one or more databases205 and one or more instances of the physical object assessment system112. In exemplary embodiments, the computing systems 200 are incommunication with the one or more computing systems 200, the one ormore servers 210, the one or more databases 205 and the one or moreinstances of the physical object assessment system 112 can be incommunication with each other via a communications network 215.

In an example embodiment, one or more portions of communications network215 can be an ad hoc network, an intranet, an extranet, a virtualprivate network (VPN), a local area network (LAN), a wireless LAN(WLAN), a wide area network (WAN), a wireless wide area network (WWAN),a metropolitan area network (MAN), a portion of the Internet, a portionof the Public Switched Telephone Network (PSTN), a cellular telephonenetwork, a wireless network, a WiFi network, a WiMax network, any othertype of network, or a combination of two or more such networks.

The one or more servers 210 includes one or more computers or processorsconfigured to communicate with the one or more computing systems 200 andthe one or more databases 205, via the network 215. The server(s) 210can host one or more applications configured to interact with the one ormore computing systems 200 and/or can facilitate access to contents ofthe one or more databases 205. The server(s) 210 can host webpagesgenerated by the one or more computing systems 200 in accordance withembodiments described herein. The databases 205 may storeinformation/data, as described herein. For example, the databases 205can include a physical object information database 220 and physicalobject metrics database 230. The databases 205 and server 210 can belocated at one or more geographically distributed locations from eachother or from the computing system 200. Alternatively, the databases 205can be included within server 210.

As a non-limiting example, the computing system 200 can receive thedecoded identifier associated with a packed physical object (e.g., thephysical object 118 shown in FIG. 1) from the readers of a first one ofthe physical object assessment systems 112 (e.g., the reader(s) 110shown in FIG. 1), x-ray images of the packed physical object from theX-ray machine of the first one of the physical object assessment systems112 (e.g., the X-ray machine 120 shown in FIG. 1), a measured weight ofthe unpacked physical object from the scale of the first one of thephysical object assessment systems 112 (e.g., the scale 102 shown inFIG. 1), and image(s) of the unpacked physical object captured by theimage capturing device of the first one of the physical objectassessment systems 112 (e.g., the image capturing device 104 shown inFIG. 1).

The computing system 200 can query the physical object informationdatabase 220 using the decoded identifier to retrieve informationassociated with the physical object. The physical objects informationdatabase 220 can return a name of the physical object, type of thephysical object, stored weight of the physical object, stored dimensionsof the physical object, a date of manufacture of the physical object, astored image of the physical object, a stored x-ray image of thephysical object, and the value of the physical object at the date ofmanufacture.

The computing system 200 can extract a set of attributes associated withthe physical object from the image using image/video analytics ormachine vision on the received image of the physical object. The typesof machine vision that can be implemented can include but are notlimited to: Stitching/Registration, Filtering, Thresholding, Pixelcounting, Segmentation, Inpainting, Edge detection, Color Analysis, Blobdiscovery & manipulation, Neural net processing, Pattern recognition,Barcode Data Matrix and “2D barcode” reading, Optical characterrecognition and Gauging/Metrology. The attributes can include but arenot limited to: estimated dimensions of the physical object, asuperficial condition of the physical object, or an age of the physicalobject.

The extracted attributes, the x-ray image and the weight of the physicalobjects can be compared to the information retrieved from the physicalobjects information database 220 to confirm and validate the physicalobject within the packaging is the same as the physical objectidentified by the identifier. For example, the computing system 200 canextract attributes such as dimensions of the physical object which canbe compared to the stored dimensions. In response to matching theextracted dimensions to the stored dimensions the computing system 200can confirm the physical object inside the packaging is the same as thephysical object identified by the identifier. In another example, thecomputing system 200 can compare the weight captured by the scale or thex-ray images captured by the x-ray machine to the stored weight and thestored image of the physical object.

Subsequent to validating the physical object, the computing system candetermine an element associated with the physical object. Based on theinformation retrieved from the physical objects information database220, the attributes extracted from the image of the physical object andthe weight of the physical object the computing system 200 can query thephysical object metrics database 230 to determine the element associatedwith the physical object. The physical objects metrics database 230 canstore elements associated with like physical objects with likeattributes. The element can be stored in the physical object informationdatabase 220.

In some embodiments, the computing system can be unable to validate thephysical object. The physical object can be damaged or incorrectlyidentified by the identifier. The extracted attributes, weight or x-rayimage may not match the information retrieved from the physical objectsinformation database 220 associated with the physical object. Theautonomous robot device (e.g., autonomous robot device 108 b shown inFIG. 1) can reroute the physical object to another conveyer belt formanual inspection.

In some embodiments, the physical object may not have an identifierlabeled on the packaging or the reader(s) may not be able to read theidentifier as the physical object is transported along the conveyerbelt. The computing system 200 can extract attributes from the imagereceived from the image capturing device. The computing system 200 canquery the physical objects information database using the extractedattributes of the physical objects, the weight of the physical objectreceived from the scale and x-ray of the physical objects to retrieveinformation associated with the physical object. The physical objectsinformation database 220 can return a name of the physical object, typeof the physical object, stored weight of the physical object, storeddimensions of the physical object, a date of manufacture of the physicalobject, and the value of the physical object at the date of manufacture.In response to receiving a predetermined threshold amount of informationfrom the physical objects information database 220 the computing system200 can validate the physical object. In response to not being able toreceive a threshold of information from the physical objects informationdatabase, the physical object can be picked up by an autonomous robotpicker and re-routed to a separate conveyer belt for manual inspection.

The computing system 200 can generate a webpage 235 in response todetermining the element associated with the physical object. Forexample, the computing system 200 can execute an automated client-sideand/or server-side script in response to determining the elementassociated with the physical object. The server-side scripts can begenerated using server side languages such as ASP, ColdFusion,JavaScript, Perl, PHP, Ruby, WebDNA and other languages. The client-sidescripts can be generated using client-side languages such as JavaScriptor ActionScript. The webpage 235 can include the physical objectinformation, the image of the physical object and the determined elementof the physical object. The computing system 200 can receive input froma user associated with the element of the physical object and theelement can dynamically change in the physical object informationdatabase 220 based on the input. In response to the element changing inthe physical object information database 220, the webpage 235 candynamically change the element on the webpage.

As a non-limiting example, the physical object assessment system 112 canbe part of an automated online appraisal and sale/auction system. Thefacility can receive a packaged product a user wishes to place on salein an auction, on a conveyer belt (e.g., the conveyor belt 100 shown inFIG. 1). The packaged product can have a machine-readable elementaffixed to the packaging, which can be encoded with an identifierassociated with the product. The reader(s) 110 can scan and decode themachine-readable element and transmit the identifier to the computingsystem 200. The autonomous robot picker 108 can remove the packaging ofthe product and the image capturing device can capture an image of theproduct after it has been removed from the packaging. The image can betransmitted to the computing system 200. The scale can determine aweight of the product and transmit the weight to the computing system200.

The computing system 200 can receive the identifier, the image andweight of the product. The computing system 200 can query the physicalobjects information database 220 using the identifier of the product toretrieve information about the product. The physical objects informationdatabase 220 can return name of the product, type of the product, model,brand, stored weight of the product, stored dimensions of the product,date of creation of the product, and the value of the product at thedate of creation. For example, if the product is a printer, thecomputing system 200 can determine the name of the printer, the brand ofthe printer, the type of printer, model number, the year the model wascreated, the weight of the product at the time of creation, the size anddimensions of the product at the time of creation, and the retail priceof the model of the printer when it was created.

The computing system 200 using image/video analytics can extractattributes from the image associated with the product. The attributescan include but are not limited to: estimated dimensions of the physicalobject, a condition of the physical object, or an age of the physicalobject. For example, continuing with the example of the printer asdiscussed above, the computing system 200 can determine the age andcondition of the printer by comparing the estimated dimensions and thesize and dimensions of the printer at the time of creation along withsubtracting the current year with the date of creation of the printer.The age and condition of the printer can also be determined by comparingthe determined weight received from the scale to the weight of theprinter at the time of creation. Furthermore, the computing system 200can extract from the image any marks, stains, hollow areas, paint chipsor any other deterioration to the printer to determine the age andcondition of the printer.

The computing system 200 can query the physical objects metrics database230 to determine an appraisal value of the product. The computing system200 can use the product information, the extracted attributes and theweight received from the scale to query the physical objects metricsdatabase 230. The physical objects metrics database 230 can match theproduct information, extracted attributes, and weight with an associatedappraisal value and return the appraisal value to the computing system200. For example, continuing with the printer example as discussedabove, the physical objects metrics database 230 can match theinformation associated with the printer, the attributes of the printerto an appraisal value and the weight of the printer with an appraisalvalue for printers with like information, attributes and weight. Inother embodiments, the computing system 200 can calculate the appraisalvalue of the product by calculating the depreciation of the printerbased on the information associated with the printer, the attributesassociated with the printer and the weight of the printer.

In response to determining the appraisal value of the product thecomputing system can automatically generate an auction webpage 235,placing the product on sale in the auction. The webpage 235 can includethe product information, the image of the product and the appraisalvalue of the product as the initial sale price. The sale price will bestored in the physical object information database 220.

In some embodiments, a user can place bid lower than the starting saleprice of the product using the webpage 235. In response to receiving thebid lower than the starting sale price, the sale price stored in thephysical objects database 220 can dynamically be lowered to the bidamount. The webpage 235 can reflect the change of the sale price in thephysical objects database 220.

In other embodiments, a user can place a bid higher than the startingsale price of the product using the webpage 235. In response toreceiving the bid higher than the starting sale price, the sale pricestored in the physical objects database 220 can dynamically be increasedto the bid amount. The webpage 235 can reflect the change of the saleprice in the physical objects database 220.

In other embodiments, the webpage 235 is a sale webpage. The sale pricedoes not change on the sale webpage 235.

FIG. 3 is a block diagram of an example computing device forimplementing exemplary embodiments of the present disclosure.Embodiments of the computing device 300 can implement embodiments of theautomated physical object assessment system. The computing device 300includes one or more non-transitory computer-readable media for storingone or more computer-executable instructions or software forimplementing exemplary embodiments. The non-transitory computer-readablemedia may include, but are not limited to, one or more types of hardwarememory, non-transitory tangible media (for example, one or more magneticstorage disks, one or more optical disks, one or more flash drives, oneor more solid state disks), and the like. For example, memory 306included in the computing device 300 may store computer-readable andcomputer-executable instructions or software (e.g., applications 330)for implementing exemplary operations of the computing device 300. Thecomputing device 300 also includes configurable and/or programmableprocessor 302 and associated core(s) 304, and optionally, one or moreadditional configurable and/or programmable processor(s) 302′ andassociated core(s) 304′ (for example, in the case of computer systemshaving multiple processors/cores), for executing computer-readable andcomputer-executable instructions or software stored in the memory 306and other programs for implementing exemplary embodiments of the presentdisclosure. Processor 302 and processor(s) 302′ may each be a singlecore processor or multiple core (304 and 304′) processor. Either or bothof processor 302 and processor(s) 302′ may be configured to execute oneor more of the instructions described in connection with computingdevice 300.

Virtualization may be employed in the computing device 300 so thatinfrastructure and resources in the computing device 300 may be shareddynamically. A virtual machine 312 may be provided to handle a processrunning on multiple processors so that the process appears to be usingonly one computing resource rather than multiple computing resources.Multiple virtual machines may also be used with one processor.

Memory 306 may include a computer system memory or random access memory,such as DRAM, SRAM, EDO RAM, and the like. Memory 406 may include othertypes of memory as well, or combinations thereof.

The computing device 300 can receive data from input/output devices suchas, a scanner 332, an image capturing device 334, and a scale 336.

A user may interact with the computing device 300 through a visualdisplay device 314, such as a computer monitor, which may display one ormore graphical user interfaces 316, multi touch interface 320 and apointing device 318.

The computing device 300 may also include one or more storage devices326, such as a hard-drive, CD-ROM, or other computer readable media, forstoring data and computer-readable instructions and/or software thatimplement exemplary embodiments of the present disclosure (e.g.,applications). For example, exemplary storage device 326 can include oneor more databases 328 for storing information regarding the physicalobjects. The databases 328 may be updated manually or automatically atany suitable time to add, delete, and/or update one or more data itemsin the databases. The databases 328 can include information such asphysical object information 220 and physical object metrics 230.

The computing device 300 can include a network interface 308 configuredto interface via one or more network devices 324 with one or morenetworks, for example, Local Area Network (LAN), Wide Area Network (WAN)or the Internet through a variety of connections including, but notlimited to, standard telephone lines, LAN or WAN links (for example,802.11, T1, T3, 56 kb, X.25), broadband connections (for example, ISDN,Frame Relay, ATM), wireless connections, controller area network (CAN),or some combination of any or all of the above. In exemplaryembodiments, the computing system can include one or more antennas 322to facilitate wireless communication (e.g., via the network interface)between the computing device 300 and a network and/or between thecomputing device 300 and other computing devices. The network interface308 may include a built-in network adapter, network interface card,PCMCIA network card, card bus network adapter, wireless network adapter,USB network adapter, modem or any other device suitable for interfacingthe computing device 300 to any type of network capable of communicationand performing the operations described herein.

The computing device 300 may run any operating system 310, such as anyof the versions of the Microsoft® Windows® operating systems, thedifferent releases of the Unix and Linux operating systems, any versionof the MacOS® for Macintosh computers, any embedded operating system,any real-time operating system, any open source operating system, anyproprietary operating system, or any other operating system capable ofrunning on the computing device 300 and performing the operationsdescribed herein. In exemplary embodiments, the operating system 310 maybe run in native mode or emulated mode. In an exemplary embodiment, theoperating system 310 may be run on one or more cloud machine instances.

FIG. 4 is a block diagram of the physical object assessment systemembodied as a smart auction system 400. The smart auction system 400 caninclude sensors disposed in a user's desired location, a userpreferences cloud system 404, a smart inventory cloud system 402, anauction database of items cloud system 406 and a client device 408. Theuser preferences cloud system 404 can include one or more databases 410storing the user preferences and one or more servers 412. The smartinventory cloud system 402 can include one or more databases 414 and aone or more servers 416. The auction database of items cloud system caninclude one or more databases 418 storing the products currently onauction and the associated information and one or more servers 420. Thecomputing system 422 can implement at least one instance of the userpreferences cloud system, the smart inventory cloud system and theauction database of items cloud system.

The sensors can be RFID readers disposed desired location in whichproducts are stored and RFID tags can be affixed to the products. Thesensing system can be a Passive Reader Active Tag (PRAT) in which thesystem has a passive reader which only receives radio signals fromactive tags. In other embodiments, the sensing system can be an ActiveReader Passive Tag (ARPT) in which the system has an active reader,which transmits interrogator signals and also receives authenticationreplies from passive tags. In other embodiments, the sensing system canbe an Active Reader Active Tag (ARAT) in which the system uses activetags awoken with an interrogator signal from the active reader.

A user can create their user preferences 404 in the database 410 forproducts preferred from the auction database 406 stored in the database418. The server 414 in the smart inventory cloud system 402 can receivescans of RFID tags, scanned by the RFID readers. The a smart inventorycloud system 402 can determine products that need to be replenishedbased on the RFID readers determining and indicating a low inventory ofparticular products based on the fewer RFID tags scanned. The a smartinventory cloud system 402 can generate a list of products from theauction's database 406 based on the products for which the inventory islow cross-referenced with the user preferences 404. The list of productscan be parsed into messages and sent to the client device 408. Themessages will include information on products for which the user will beable to submit bid(s) for products. The user will be presented withinformation on the lowest-or-best deals for products for which theinventory is low. The user can be notified when a desired quantity ofproducts are available in the auction database of items 406. In someembodiments, the smart auction system 400 can automatically purchase theproducts on the generated list and have it delivered to the user'saddress. In other embodiments, the user may selectively purchase theproducts on the generated product list. In some embodiments, the auctiondatabase of items 406 can determine products similar to the ones neededby the user.

In some embodiments, the sensors can be image capturing devices disposedat the desired location so that the user's products are in view of theimage capturing devices. The image capturing devices can capture imagesof the products and transfer the images to the server 414 in the smartinventory cloud system 402. The server 414 can execute a videorecognition application which uses video analytics to determineinventory of a particular product.

As a non-limiting example, a user can store bottles of laundry detergentin a storage room affixed with RFID tags. RFID readers can be disposedin the storage room. The bottles can be removed as they are used,causing fewer RFID tags being read by the RFID readers. The laundrydetergent can be linked to a user's smart-inventory cloud system 402.The smart inventory cloud system 402 can detect low-inventory of thelaundry detergent based on fewer RFID tags read by the RFID readers. Thesmart inventory cloud system 404 can query the laundry detergents on theauction inventory database of items 402 and further cross-reference thepreferred laundry detergents with the user's preferences to generate alist of possible laundry detergents for purchase. The smart auctionsystem 400 will present the list of possible laundry detergents forpurchase to the user. In some embodiments, the user can selectivelypurchase the desired laundry detergent. In other embodiments, the smartauction system 400 can automatically purchase the desired laundrydetergent.

FIG. 5 illustrates a block diagram of the physical object assessmentsystem embodied as an auction system using decentralized currencyaccording the present disclosure. The auction system using decentralizedcurrency 500 can include an asset broker 502, an asset agent 504, anasset locker 506 and a client device 508. The asset broker 502 can be acloud system including a one or more databases 510 and one or moreservers 512. The asset locker 504 can be a cloud system including one ormore databases 514 and one or more servers 516. The asset agent 506 canhave one or more database 518 and one or more servers 520. A computingsystem 522 can implement at least one instance of the asset broker 502,asset locker 504 and asset agent 506. As a non-limiting example, a usercan transfer currency from the financial institution to the asset locker506. A user can submit bid on a product on auction using the clientdevice 508. Currency is withheld or prevented from dissipating theirassets from the user's asset locker 506. If the user loses the bid, thecurrency is distributed or allowed to dissipate the assets from theuser's asset locker 506. If the user wins the bid, the withheld currencyis distributed to the auctioneer and/or seller. In another embodiment,if the client wins the bid, the frozen currency is distributed andfrozen within the auctioneer's or seller's Asset Locker until producthas been received by the user. In some embodiments, if the user does notwin the bid, the user can be presented recommended products similar tothe product bid on by the user.

FIG. 6 illustrates a block diagram of the smart coin system of theauction system using decentralized currency according to the presentdisclosure. The auction system using decentralized currency can usesmart coins as currency used for the auction. In exemplary embodiments,the smart coin module 600 can receive a request for a NFC transactionfrom a user 602. The smart coin module 600 can convert the currency 604deposited by the user into smart coin using a foreign exchange module606. The smart coin module can deposit the exchanged currency in theuser's asset locker (e.g. user's asset locker 506 shown in FIG. 5).

FIG. 7 illustrates a flowchart of the physical object assessment systemaccording to the present disclosure. In operation 700, a conveyer belt(e.g., the conveyor belt 100 shown in FIG. 1) receives, transports, andsupports, a physical object (e.g., the physical object 118 shown in FIG.1). As mentioned above, the conveyer belt 100 can include stations alongthe length of the belt. A first station can be a there can be an opticalscanning station using a reader (s) (e.g., the reader(s) 110 shown inFIG. 1), a second station can be x-ray machine (e.g., the x-ray machine120 shown in FIG. 1), at a third station there can be a unpackingstation by an autonomous robot picker (e.g., the autonomous robot picker108 a shown in FIG. 1), at a fourth station a scale (e.g., the scale 102shown in FIG. 1), and at a fifth station there can be an image capturingstation using an image capturing device (e.g., the image capturingdevice 104 shown in FIG. 1). The physical object is associated with amachine-readable element (e.g., the machine-readable element 116 shownin FIG. 1) encoded with an identifier corresponding to the physicalobject. The physical object is enclosed in packaging (e.g., thepackaging 106 shown in FIG. 1). The machine-readable element is affixedto the packaging of the physical object. The machine-readable elementcan be a barcode or QR code.

In operation 702, a reader(s) disposed with respect to the conveyerbelt, scans the machine-readable element and decodes the identifierencoded within the machine-readable element. The reader(s) can be anoptical scanner configured to read barcodes or QR codes.

In operation 704, an autonomous robot picker removes the packaging fromthe physical object. In operation 706, an image capturing devicedisposed with respect to the conveyer belt, captures an image of thephysical object. The image capturing device can capture a moving imageor a still image of the physical object.

In operation 708, a scale coupled to the conveyer belt, determines theweight of the physical object.

In operation 710, a computing system (e.g., the computing system 200shown in FIG. 2) operatively coupled to the reader(s), image capturingdevice and scale queries the physical objects information database(e.g., the physical objects information database 220 shown in FIG. 2)using the identifier extracted from the machine-readable element by thereader(s) to retrieve information regarding the physical object. Inoperation 712, computing system extracts a set of attributes associatedwith the physical object from the image of the physical object usingvideo analytics. In operation 714, the computing system identifies anelement associated with the physical object based on the retrievedinformation regarding the physical object, the set of attributesassociated with the physical object and the weight of the physicalobject. In operation 716, the computing system creates a webpageincluding the information, the set of attributes associated with thephysical object, the image of the physical object and the element.

FIG. 8 illustrates a flowchart of the smart auction system according tothe present disclosure. In operation 800, the user can create userpreferences for desired products from the database (e.g., the database418 shown in FIG. 4) of the auction database of items cloud system(e.g., the auction database of items cloud system 406 shown in FIG. 4).The user preferences can be stored in the database (e.g., the database410 shown in FIG. 4) of the user preferences cloud system (e.g., userpreferences cloud system 404 shown in FIG. 4). The products in thedatabase of the auction database of items cloud system can be placed onauction using the physical object assessment system (e.g., physicalobject assessment system 112 shown in FIG. 1).

In operation 802, RFID readers can read RFID tags affixed on products ina specific location. In the smart auction system, RFID readers can bedisposed in a particular location in which products for which the userdesires to monitor inventory for are disposed. The product can beaffixed with RFID tags.

In operation 804, the RFID readers can transmit the scanned RFID tags tothe smart inventory cloud system (e.g., smart inventory cloud system 402shown in FIG. 4). The smart inventory cloud system can keep track of theinventory of the products based on the received scans.

In operation 806, the smart inventory cloud system can determine aproduct has low inventory based on the received scans. In operation 808,the smart inventory cloud system can query the database of the userpreferences cloud system to retrieve a list of preferred products. Thesmart inventory cloud system can cross-reference the list of preferredproducts with the products on sale in the auction database of itemscloud system. The smart inventory cloud system can generate a short listof products based on the cross references. The smart inventory cloudsystem can rank the short list of products based on closest matchedproduct to the product needing replenishment and based on the number ofproducts needed.

In operation 810, the smart inventory cloud system can determine whetherthe user has selected automated purchase. In response to determining theuser has selected automated purchase, in operation 812 the smartinventory cloud system automatically purchases the product for the user.Otherwise in operation 814, the user is presented the short list ofproducts to select a product to purchase.

In describing exemplary embodiments, specific terminology is used forthe sake of clarity. For purposes of description, each specific term isintended to at least include all technical and functional equivalentsthat operate in a similar manner to accomplish a similar purpose.Additionally, in some instances where a particular exemplary embodimentincludes a multiple system elements, device components or method steps,those elements, components or steps may be replaced with a singleelement, component or step. Likewise, a single element, component orstep may be replaced with multiple elements, components or steps thatserve the same purpose. Moreover, while exemplary embodiments have beenshown and described with references to particular embodiments thereof,those of ordinary skill in the art will understand that varioussubstitutions and alterations in form and detail may be made thereinwithout departing from the scope of the present disclosure. Furtherstill, other aspects, functions and advantages are also within the scopeof the present disclosure.

Exemplary flowcharts are provided herein for illustrative purposes andare non-limiting examples of methods. One of ordinary skill in the artwill recognize that exemplary methods may include more or fewer stepsthan those illustrated in the exemplary flowcharts, and that the stepsin the exemplary flowcharts may be performed in a different order thanthe order shown in the illustrative flowcharts.

We claim:
 1. An autonomous distributed computing system comprising: aconveyer belt configured to receive, support, and transport a physicalobject, wherein the physical object is associated with amachine-readable element encoded with an identifier corresponding to thephysical object; a scanner disposed with respect to the conveyer beltand configured to scan the machine-readable element of the physicalobject and decode the machine-readable element to extract theidentifier; an image capturing device disposed with respect to theconveyer belt and configured to capture an image of the physical object;a scale operatively coupled to the conveyer belt and configured todetermine a weight of the physical object; a computing system includinga server and a database operatively coupled to the scanner, the imagecapturing device, and the scale, the computing system being programmedto (i) query the database using the identifier extracted from themachine-readable element by the scanner to retrieve informationregarding the physical object from one or more tables in the database,(ii) extract a set of attributes associated with the physical objectfrom the image of the physical object, (iii) identify an elementassociated with the physical object based on the retrieved informationregarding the physical object, the set of attributes associated with thephysical object and the weight of the physical object, and (iv)automatically create a webpage associated with the physical object whichwas transported by the conveyer belt system, the webpage including theretrieved information, the set of attributes extracted from the image ofthe physical object, and the element, and an autonomous robot pickerconfigured to remove the physical object from packaging enclosing thephysical object, subsequent to the scanner scanning the machine-readableelement and prior to triggering the image capturing device to capturethe image of the physical object, wherein the set of attributes includesat least one of: estimated dimensions of the physical object, acondition of the physical object, or an age of the physical object. 2.The system in claim 1, wherein the information associated with thephysical object includes at least one: a name of the physical object, atype of the physical object, a stored weight of the physical object, orstored dimensions of the physical object.
 3. The system in claim 1,wherein the autonomous robot picker is operable to place the physicalobject on to the conveyer belt or remove the physical object from theconveyor belt.
 4. The system in claim 3, wherein the machine-readableelement is affixed to the packaging.
 5. The system in claim 1, whereinthe computing system inserts the image of the physical object capturedby the image capturing device into the webpage.
 6. The system in claim1, wherein in response to identifying the element associated with thephysical object based on the retrieved information regarding thephysical object, the set of attributes associated with the physicalobject and the weight of the physical object, the element is stored inthe database.
 7. The system in claim 6, wherein the element stored inthe database dynamically changes based on an input received by thecomputing system.
 8. The system in claim 7, wherein in response to theelement stored in the database dynamically changing based on an inputreceived by the computing system, the webpage is updated to reflect thechange in the element.
 9. An autonomous distributed computing methodcomprising: receiving, a physical object by a conveyor belt, thephysical object being associated with a machine-readable element encodedwith an identifier corresponding to the physical object; transportingthe physical object via the conveyer belt; scanning, via a scannerdisposed with respect to the conveyer belt, the machine-readable elementof the physical object, decoding, via the scanner, the machine-readableelement to extract the identifier; capturing, via an image capturingdevice disposed with respect to the conveyer belt, an image of thephysical object; determining, via a scale operatively coupled to theconveyer belt, a weight of the physical object; querying, via acomputing system including a server and a database operatively coupledto the scanner, the image capturing device, and the scale, the databaseusing the identifier extracted from the machine-readable element by thescanner to retrieve information regarding the physical object from oneor more tables in the database; extracting, via the computing system, aset of attributes associated with the physical object from the image ofthe physical object; identifying, via the computing system, an elementassociated with the physical object based on the retrieved informationregarding the physical object, the set of attributes associated with thephysical object and the weight of the physical object; automaticallycreating, via the computing system, a webpage associated with thephysical object which was transported by the conveyer belt system, thewebpage including the retrieved information, the set of attributesextracted from the image of the physical object, and the element; andremoving, via an autonomous robot picker, the physical object frompackaging enclosing the physical object, subsequent to the scannerscanning the machine-readable element and prior to triggering the imagecapturing device to capture the image of the physical object, whereinthe set of attributes includes at least one of: estimated dimensions ofthe physical object, a condition of the physical object, or an age ofthe physical object.
 10. The method of claim 9, wherein the informationassociated with the physical object includes at least one: a name of thephysical object, a type of the physical object, a stored weight of thephysical object, or a stored dimensions of the physical object.
 11. Themethod of claim 9, further comprising at least one of placing thephysical object on to the conveyer belt by the autonomous robot pickeror removing the physical object from the conveyor belt by the autonomousrobot picker.
 12. The method of claim 11, wherein the machine-readableelement is affixed to the packaging.
 13. The method of claim 9, furthercomprising inserting the image of the physical object captured by theimage capturing device into the webpage.
 14. The method of claim 9,wherein in response to identifying the element associated with thephysical object based on the retrieved information regarding thephysical object, the set of attributes associated with the physicalobject and the weight of the physical object, the method furthercomprises storing the element in the database by the computing system.15. The method of claim 14, further comprising dynamically changing theelement stored in the database based on an input received by thecomputing system.
 16. The method of claim 15, wherein in response to theelement stored in the database dynamically changing based on an inputreceived by the computing system, the method further comprises updatingthe webpage to reflect the change in the element.